OpenRaiser/Intern-Atlas huggingface dataset:
Building Program Vector Representations for Deep Learning
Venue: arXiv cs.SE 2014
Year: 2014

Deep learning has made significant breakthroughs in various fields of artificial intelligence. Advantages of deep learning include the ability to capture highly complicated features, weak involvement of human engineering, etc. However, it is still virtually impossible to use deep learning to analyze programs since deep architectures cannot be trained effectively with pure back propagation. In this pioneering paper, we propose the "coding criterion" to build program vector representations, which are the premise of deep learning for program analysis. Our representation learning approach directly makes deep learning a reality in this new field. We evaluate the learned vector representations both qualitatively and quantitatively. We conclude, based on the experiments, the coding criterion is successful in building program representations. To evaluate whether deep learning is beneficial for program analysis, we feed the representations to deep neural networks, and achieve higher accuracy in the program classification task than "shallow" methods, such as logistic regression and the support vector machine. This result confirms the feasibility of deep learning to analyze programs. It also gives primary evidence of its success in this new field. We believe deep learning will become an outstanding technique for program analysis in the near future.
Static Enforcement of Role-Based Access Control
Venue: arXiv cs.SE 2014
Year: 2014

We propose a new static approach to Role-Based Access Control (RBAC) policy enforcement. The static approach we advocate includes a new design methodology, for applications involving RBAC, which integrates the security requirements into the system's architecture. We apply this new approach to policies restricting calls to methods in Java applications. We present a language to express RBAC policies on calls to methods in Java, a set of design patterns which Java programs must adhere to for the policy to be enforced statically, and a description of the checks made by our static verifier for static enforcement.
Energy Harvesting for Secure OFDMA Systems
Venue: arXiv cs.IT 2014
Year: 2014

Energy harvesting and physical-layer security in wireless networks are of great significance. In this paper, we study the simultaneous wireless information and power transfer (SWIPT) in downlink orthogonal frequency-division multiple access (OFDMA) systems, where each user applies power splitting to coordinate the energy harvesting and information decoding processes while secrecy information requirement is guaranteed. The problem is formulated to maximize the aggregate harvested power at the users while satisfying secrecy rate requirements of all users by subcarrier allocation and the optimal power splitting ratio selection. Due to the NP-hardness of the problem, we propose an efficient iterative algorithm. The numerical results show that the proposed method outperforms conventional methods.
A 4/3-approximation algorithm for finding a spanning tree to maximize its internal vertices
Venue: arXiv cs.DS 2014
Year: 2014

This paper focuses on finding a spanning tree of a graph to maximize the number of its internal vertices. We present an approximation algorithm for this problem which can achieve a performance ratio $\frac{4}{3}$ on undirected simple graphs. This improves upon the best known approximation algorithm with performance ratio $\frac{5}{3}$ before. Our algorithm benefits from a new observation for bounding the number of internal vertices of a spanning tree, which reveals that a spanning tree of an undirected simple graph has less internal vertices than the edges a maximum path-cycle cover of that graph has. We can also give an example to show that the performance ratio $\frac{4}{3}$ is actually tight for this algorithm. To decide how difficult it is for this problem to be approximated, we show that finding a spanning tree of an undirected simple graph to maximize its internal vertices is Max-SNP-Hard.
DW&C:Dollops Wise Curtail IPv4/IPv6 Transition Mechanism using NS2
Venue: arXiv cs.NI 2014
Year: 2014

BD-SIIT and DSTM are widely deployed IPv4/IPv6 Transition mechanism to improve the performance of the computer network in terms of Throughput,End to End Delay(EED) and Packet Drop Rate(PDR).In this journal paper we have Implemented and Compared the Performance Issues of our newly proposed Dollops Wise Curtail(DW&C)IPv4/IPv6 Migration Mechanism with BD-SIIT and DSTM in NS2. Implementation and Comparison Performance Analysis between Dollops Wise Curtail,BD-SIIT and DSTM shows that Dollops Wise Curtail IPv4/IPv6 migration algorithm performance outperforms than BD-SIIT and DSTM.Based on extensive simulations,we show that DW&C algorithm reduces the Packet Drop Rate(PDR),End to End Delay(EED) and achieves better Throughput than BD-SIIT and DSTM.In our research work observation,the performance metrics such as Throughput,EED and PLR for DW&C,BD-SIIT and DSTM are measured using TCP,UDP,FTP and CBR Traffics
A Reputation-Based Model for Decision-Making in Online Social Networks
Venue: arXiv cs.SI 2014
Year: 2014

The online exchange of social recognition including, for instance, the Facebook "like" appears to produce a scarce allocation without a clear utility function defined for anyone involved. Given the importance attached to such digital commodities by both users and advertisers, it is of interest to study the forces governing their economics. Here we propose a centrality measure akin to eigenvector centrality to describe an individual's perceived importance in an online social network. It is shown in silico that strategically maximizing this prestige metric results in finite nontrivial rates of "like" endowment. Furthermore, it is found that systems of reputation-seeking agents are supported most robustly by networks with the features of real human societies including preferential attachment and the small-world property. We conclude that the incentive system studied here can produce realistic behavior and may therefore provide a framework for a more general model of decision-making in online communities.
Concept-Oriented Programming: References, Classes and Inheritance Revisited
Venue: arXiv cs.SE 2014
Year: 2014

The main goal of concept-oriented programming (COP) is describing how objects are represented and accessed. It makes references (object locations) first-class elements of the program responsible for many important functions which are difficult to model via objects. COP rethinks and generalizes such primary notions of object-orientation as class and inheritance by introducing a novel construct, concept, and a new relation, inclusion. An advantage is that using only a few basic notions we are able to describe many general patterns of thoughts currently belonging to different programming paradigms: modeling object hierarchies (prototype-based program-ming), precedence of parent methods over child methods (inner methods in Beta), modularizing cross-cutting con-cerns (aspect-oriented programming), value-orientation (functional programming). Since COP remains backward compatible with object-oriented programming, it can be viewed as a perspective direction for developing a simple and natural unified programming model.
On the Simulatability Condition in Key Generation Over a Non-authenticated Public Channel
Venue: arXiv cs.CR 2014
Year: 2014

Simulatability condition is a fundamental concept in studying key generation over a non-authenticated public channel, in which Eve is active and can intercept, modify and falsify messages exchanged over the non-authenticated public channel. Using this condition, Maurer and Wolf showed a remarkable "all or nothing" result: if the simulatability condition does not hold, the key capacity over the non-authenticated public channel will be the same as that of the case with a passive Eve, while the key capacity over the non-authenticated channel will be zero if the simulatability condition holds. However, two questions remain open so far: 1) For a given joint probability mass function (PMF), are there efficient algorithms (polynomial complexity algorithms) for checking whether the simulatability condition holds or not?; and 2) If the simulatability condition holds, are there efficient algorithms for finding the corresponding attack strategy? In this paper, we answer these two open questions affirmatively. In particular, for a given joint PMF, we construct a linear programming (LP) problem and show that the simulatability condition holds \textit{if and only if} the optimal value obtained from the constructed LP is zero. Furthermore, we construct another LP and show that the minimizer of the newly constructed LP is a valid attack strategy. Both LPs can be solved with a polynomial complexity.
Robust Chaos Generation on the Basis of Symmetry Violations in Attractors
Venue: arXiv cs.SY 2014
Year: 2014

We present a method for generating robust chaos. It is based on the search algorithm weak symmetry violation in the reconstructed attractor. On its basis the smooth functions in the form of a system of finite-difference equations. To ensure robust chaos generator introduced piecewise continuous member. The simulation results are given in the report.
On the optimality of shape and data representation in the spectral domain
Venue: arXiv cs.CV 2014
Year: 2014

A proof of the optimality of the eigenfunctions of the Laplace-Beltrami operator (LBO) in representing smooth functions on surfaces is provided and adapted to the field of applied shape and data analysis. It is based on the Courant-Fischer min-max principle adapted to our case. % The theorem we present supports the new trend in geometry processing of treating geometric structures by using their projection onto the leading eigenfunctions of the decomposition of the LBO. Utilisation of this result can be used for constructing numerically efficient algorithms to process shapes in their spectrum. We review a couple of applications as possible practical usage cases of the proposed optimality criteria. % We refer to a scale invariant metric, which is also invariant to bending of the manifold. This novel pseudo-metric allows constructing an LBO by which a scale invariant eigenspace on the surface is defined. We demonstrate the efficiency of an intermediate metric, defined as an interpolation between the scale invariant and the regular one, in representing geometric structures while capturing both coarse and fine details. Next, we review a numerical acceleration technique for classical scaling, a member of a family of flattening methods known as multidimensional scaling (MDS). There, the optimality is exploited to efficiently approximate all geodesic distances between pairs of points on a given surface, and thereby match and compare between almost isometric surfaces. Finally, we revisit the classical principal component analysis (PCA) definition by coupling its variational form with a Dirichlet energy on the data manifold. By pairing the PCA with the LBO we can handle cases that go beyond the scope defined by the observation set that is handled by regular PCA.
A Binary Schema and Computational Algorithms to Process Vowel-based Euphonic Conjunctions for Word Searches
Venue: arXiv cs.CL 2014
Year: 2014

Comprehensively searching for words in Sanskrit E-text is a non-trivial problem because words could change their forms in different contexts. One such context is sandhi or euphonic conjunctions, which cause a word to change owing to the presence of adjacent letters or words. The change wrought by these possible conjunctions can be so significant in Sanskrit that a simple search for the word in its given form alone can significantly reduce the success level of the search. This work presents a representational schema that represents letters in a binary format and reduces Paninian rules of euphonic conjunctions to simple bit set-unset operations. The work presents an efficient algorithm to process vowel-based sandhis using this schema. It further presents another algorithm that uses the sandhi processor to generate the possible transformed word forms of a given word to use in a comprehensive word search.
Computational Algorithms Based on the Paninian System to Process Euphonic Conjunctions for Word Searches
Venue: arXiv cs.CL 2014
Year: 2014

Searching for words in Sanskrit E-text is a problem that is accompanied by complexities introduced by features of Sanskrit such as euphonic conjunctions or sandhis. A word could occur in an E-text in a transformed form owing to the operation of rules of sandhi. Simple word search would not yield these transformed forms of the word. Further, there is no search engine in the literature that can comprehensively search for words in Sanskrit E-texts taking euphonic conjunctions into account. This work presents an optimal binary representational schema for letters of the Sanskrit alphabet along with algorithms to efficiently process the sandhi rules of Sanskrit grammar. The work further presents an algorithm that uses the sandhi processing algorithm to perform a comprehensive word search on E-text.
Efficient Synchronization Stability Metrics for Fault Clearing
Venue: arXiv cs.SY 2014
Year: 2014

Direct methods can provide rapid screening of the dynamical security of large numbers fault and contingency scenarios by avoiding extensive time simulation. We introduce a computationally-efficient direct method based on optimization that leverages efficient cutting plane techniques. The method considers both unstable equilibrium points and the effects of additional relay tripping on dynamical security\cite{01SH}. Similar to other direct methods, our approach yields conservative results for dynamical security, however, the optimization formulation potentially lends itself to the inclusion of additional constraints to reduce this conservatism.
Distributed Rate Adaptation and Power Control in Fading Multiple Access Channels
Venue: arXiv cs.IT 2014
Year: 2014

Traditionally, the capacity region of a coherent fading multiple access channel (MAC) is analyzed in two popular contexts. In the first, a centralized system with full channel state information at the transmitters (CSIT) is assumed, and the communication parameters like transmit power and data-rate are jointly chosen for every fading vector realization. On the other hand, in fast-fading links with distributed CSIT, the lack of full CSI is compensated by performing ergodic averaging over sufficiently many channel realizations. Notice that the distributed CSI may necessitate decentralized power-control for optimal data-transfer. Apart from these two models, the case of slow-fading links and distributed CSIT, though relevant to many systems, has received much less attention. In this paper, a block-fading AWGN MAC with full CSI at the receiver and distributed CSI at the transmitters is considered. The links undergo independent fading, but otherwise have arbitrary fading distributions. The channel statistics and respective long-term average transmit powers are known to all parties. We first consider the case where each encoder has knowledge only of its own link quality, and not of others. For this model, we compute the adaptive capacity region, i.e. the collection of average rate-tuples under block-wise coding/decoding such that the rate-tuple for every fading realization is inside the instantaneous MAC capacity region. The key step in our solution is an optimal rate allocation function for any given set of distributed power control laws at the transmitters. This also allows us to characterize the optimal power control for a wide class of fading models. Further extensions are also proposed to account for more general CSI availability at the transmitters.
DISA at ImageCLEF 2014 Revised: Search-based Image Annotation with DeCAF Features
Venue: arXiv cs.IR 2014
Year: 2014

This paper constitutes an extension to the report on DISA-MU team participation in the ImageCLEF 2014 Scalable Concept Image Annotation Task as published in [3]. Specifically, we introduce a new similarity search component that was implemented into the system, report on the results achieved by utilizing this component, and analyze the influence of different similarity search parameters on the annotation quality.
Offline Trace Checking of Quantitative Properties of Service-Based Applications
Venue: arXiv cs.SE 2014
Year: 2014

Service-based applications are often developed as compositions of partner services. A service integrator needs precise methods to specify the quality attributes expected by each partner service, as well as effective techniques to verify these attributes. In previous work, we identified the most common specification patterns related to provisioning service-based applications and developed an expressive specification language (SOLOIST) that supports them. SOLOIST is an extension of metric temporal logic with aggregate temporal modalities that can be used to write quantitative temporal properties. In this paper we address the problem of performing offline checking of service execution traces against quantitative requirements specifications written in SOLOIST. We present a translation of SOLOIST into CLTLB(D), a variant of linear temporal logic, and reduce the trace checking of SOLOIST to bounded satisfiability checking of CLTLB(D), which is supported by ZOT, an SMT-based verification toolkit. We detail the results of applying the proposed offline trace checking procedure to different types of traces, and compare its performance with previous work.
Lurking in Social Networks: Topology-based Analysis and Ranking Methods
Venue: arXiv cs.SI 2014
Year: 2014

The massive presence of silent members in online communities, the so-called lurkers, has long attracted the attention of researchers in social science, cognitive psychology, and computer-human interaction. However, the study of lurking phenomena represents an unexplored opportunity of research in data mining, information retrieval and related fields. In this paper, we take a first step towards the formal specification and analysis of lurking in social networks. We address the new problem of lurker ranking and propose the first centrality methods specifically conceived for ranking lurkers in social networks. Our approach utilizes only the network topology without probing into text contents or user relationships related to media. Using Twitter, Flickr, FriendFeed and GooglePlus as cases in point, our methods' performance was evaluated against data-driven rankings as well as existing centrality methods, including the classic PageRank and alpha-centrality. Empirical evidence has shown the significance of our lurker ranking approach, and its uniqueness in effectively identifying and ranking lurkers in an online social network.
Differential analysis of nonlinear systems: revisiting the pendulum example
Venue: arXiv cs.SY 2014
Year: 2014

Differential analysis aims at inferring global properties of nonlinear behaviors from the local analysis of the linearized dynamics. The paper motivates and illustrates the use of differential analysis on the nonlinear pendulum model, an archetype example of nonlinear behavior. Special emphasis is put on recent work by the authors in this area, which includes a differential Lyapunov framework for contraction analysis and the concept of differential positivity.
An Efficient List Decoder Architecture for Polar Codes
Venue: arXiv cs.AR 2014
Year: 2014

Long polar codes can achieve the symmetric capacity of arbitrary binary-input discrete memoryless channels under a low complexity successive cancelation (SC) decoding algorithm. However, for polar codes with short and moderate code length, the decoding performance of the SC algorithm is inferior. The cyclic redundancy check (CRC) aided successive cancelation list (SCL) decoding algorithm has better error performance than the SC algorithm for short or moderate polar codes. In this paper, we propose an efficient list decoder architecture for the CRC aided SCL algorithm, based on both algorithmic reformulations and architectural techniques. In particular, an area efficient message memory architecture is proposed to reduce the area of the proposed decoder architecture. An efficient path pruning unit suitable for large list size is also proposed. For a polar code of length 1024 and rate $\frac{1}{2}$, when list size $L=2$ and 4, the proposed list decoder architecture is implemented under a TSMC 90nm CMOS technology. Compared with the list decoders in the literature, our decoder achieves 1.33 to 1.96 times hardware efficiency.
A Fast Convergence Density Evolution Algorithm for Optimal Rate LDPC Codes in BEC
Venue: arXiv cs.IT 2014
Year: 2014

We derive a new fast convergent Density Evolution algorithm for finding optimal rate Low-Density Parity-Check (LDPC) codes used over the binary erasure channel (BEC). The fast convergence property comes from the modified Density Evolution (DE), a numerical method for analyzing the behavior of iterative decoding convergence of a LDPC code. We have used the method of [16] for designing of a LDPC code with optimal rate. This has been done for a given parity check node degree distribution, erasure probability and specified DE constraint. The fast behavior of DE and found optimal rate with this method compare with the previous DE constraint.
Calculation of Generalized Polynomial-Chaos Basis Functions and Gauss Quadrature Rules in Hierarchical Uncertainty Quantification
Venue: arXiv cs.CE 2014
Year: 2014

Stochastic spectral methods are efficient techniques for uncertainty quantification. Recently they have shown excellent performance in the statistical analysis of integrated circuits. In stochastic spectral methods, one needs to determine a set of orthonormal polynomials and a proper numerical quadrature rule. The former are used as the basis functions in a generalized polynomial chaos expansion. The latter is used to compute the integrals involved in stochastic spectral methods. Obtaining such information requires knowing the density function of the random input {\it a-priori}. However, individual system components are often described by surrogate models rather than density functions. In order to apply stochastic spectral methods in hierarchical uncertainty quantification, we first propose to construct physically consistent closed-form density functions by two monotone interpolation schemes. Then, by exploiting the special forms of the obtained density functions, we determine the generalized polynomial-chaos basis functions and the Gauss quadrature rules that are required by a stochastic spectral simulator. The effectiveness of our proposed algorithm is verified by both synthetic and practical circuit examples.
On the fundamental limitations of performance for distributed decision-making in robotic networks
Venue: arXiv cs.MA 2014
Year: 2014

This paper studies fundamental limitations of performance for distributed decision-making in robotic networks. The class of decision-making problems we consider encompasses a number of prototypical problems such as average-based consensus as well as distributed optimization, leader election, majority voting, MAX, MIN, and logical formulas. We first propose a formal model for distributed computation on robotic networks that is based on the concept of I/O automata and is inspired by the Computer Science literature on distributed computing clusters. Then, we present a number of bounds on time, message, and byte complexity, which we use to discuss the relative performance of a number of approaches for distributed decision-making. From a methodological standpoint, our work sheds light on the relation between the tools developed by the Computer Science and Controls communities on the topic of distributed algorithms.